Event-Driven Processing

Computation triggered by events (spikes) rather than synchronized clock cycles — the processing paradigm of neuromorphic systems.

In conventional computing, all circuits update every clock tick regardless of whether data changed. In event-driven systems, components are dormant until they receive input. This asynchronous approach dramatically reduces power consumption for sparse, temporally structured data.

Systems Connection

Event-driven processing exemplifies how structure enables function. By organizing computation around discrete flows (spikes) rather than continuous clock signals, neuromorphic systems achieve energy efficiency that emerges from their architecture rather than their algorithms.

Key Benefits

• Power efficiency — idle circuits consume no energy
• Low latency — no waiting for clock cycles
• Natural fit — matches temporal structure of real-world data

See Also

• Neuromorphics — parent domain
• Spike — the triggering events
• Neuromorphic Hardware — implements event-driven computation
• In-Memory Computing — complementary paradigm